Why does this model have 12 parameters?
You have 3 inputs going to 3 nodes in the input layer. Each connection has a weight so you have  3 X 3 =9 weights. Plus each node has a bias weight so that adds 3 more weights for a total of 12. Your output layer has 3 inputs and is a single node so you have 3 weights for the inputs to the node plus a bias weight for a total of 4. So the total weights in your network is 16.